ENGINEERING
ENGINEERS AT THE EDGE: HOW AUTOMATION AND AI UPGRADE ENVIRONMENTAL MANAGEMENT AND PRODUCTION
ENGINEERS AT THE EDGE: HOW AUTOMATION AND AI UPGRADE ENVIRONMENTAL MANAGEMENT AND PRODUCTION
PERFORMANCE FROM SHOPFLOOR DATA TO PREDICTIVE DECISIONS
PERFORMANCE FROM SHOPFLOOR DATA TO PREDICTIVE DECISIONS
AspartofHumanCapital’songoingseriesonexecutive leadershipandindustrytransformation,AnaPaula Montanha,Editor-in-ChiefofHumanCapitalCareer TrendsMagazine,interviewedtheexpertThomaz AntunesEspindolaMendesdaMota,aBrazilianProcess Engineerspecializinginproductionefficiency,process optimization,andenvironmentalmanagement.
Mr Motahasbuiltareputationforexcellence,combining engineeringprecisionwithstrategicmanagement Inthis conversation,Mr Motashareshowhisintegrated approachtoleadership,sustainability,technology,and innovationcontinuestoshapethemodernizationofthe sector,drivingefficiency,economicimpact,andvalue creationinanincreasinglycompetitivemarket
INTRODUCTION
TheUnitedStatesiswitnessinganacceleratingdemand forprocessengineerswhocanuniteautomation,data science,andsustainabilitytostrengthenproductive resilience AccordingtotheUS BureauofLaborStatistics forIndustrialEngineers,aclassificationthatincludesmany processengineeringroles,employmentisprojectedto grow11%from2024to2034,withabout25,200openings annually Themedianannualwagewas$101,140inMay 2024,underscoringthestrategicrelevanceofengineers whooptimizeproductionwhilemeetingenvironmental andsafetyrequirements
Thatneedisamplifiedbythecountry’senvironmental obligations TheUS EnvironmentalProtectionAgency (2024a)reportedthat7,544industrialfacilitiesemitted approximately258billionmetrictonsofCO₂-equivalentin 2023undertheGreenhouseGasReportingProgram (GHGRP) Thesefiguresmakeclearthatdataintegrity, automation,andpredictiveanalyticsarecentralto addressingclimategoalswhilemaintainingproductivity
ProcessengineerssuchasThomazAntunesEspindola MendesdaMota,whomergeproductionengineeringwith environmentalmanagement,standattheforefrontofthis evolution,transformingrawdataintooperationalforesight thatsupportscleaner,moreefficient,andcompliant manufacturingprocesses
INDUSTRYTRENDSANDMARKETANALYSIS
TheUS manufacturingsectorisundergoinganewindustrial revolutionpoweredbyautomation,artificialintelligence(AI), andpredictivemaintenance(PdM) TheNationalInstituteof StandardsandTechnologyemphasizesthattrustworthy, validateddataandtransparentalgorithmsareessentialforsafe AIadoptioninmanufacturing Likewise,theUS Departmentof Energy’sFederalEnergyManagementProgram(DOEFEMP, 2024)notesthatmaturepredictive-maintenanceprograms delivermeasurablereliabilitygainsandsignificant maintenance-costreductionscomparedwithrun-to-failure approaches
TheUS EnergyInformationAdministration(2025)reportsthat manufacturingusedroughly207quadrillionBTUofenergyin 2022,accountingforabout25%oftotalUS energyuse,while reducingenergyintensity(energyperunitofoutput)bymore than50%since1998.
Theseforcesarereshapingtheskillslandscape,engineers mustnowintegrateISO-certifiedmanagementsystems,realtimeanalytics,andsustainabilitymetricsintocohesivedigital frameworks.Thisconvergencedefinesthenewprocess engineer:aprofessionalequallyversedinprocessoptimization andenvironmentalaccountability
CAREERPROFILEANDMEASURABLEIMPACT
ThomazAntunesEspindolaMendesdaMotarepresentsthis newgenerationofdata-literate,sustainability-focused engineers WithadualacademicfoundationinProduction EngineeringandEnvironmentalManagement,hecombines processoptimization,wastemanagementexpertise,logistics, andISOauditingtodriveperformanceandcompliance simultaneously
Thomaz’sprojectsdemonstratehowAIcantranslate processdataintomeasurableenvironmentaland operationalgains Inenvironmentalmanagement,he shareshisinsightsonhowAI-basedmonitoringsystems linkparameterssuchastemperature,energy consumption,andwastegenerationtoanomaly-detection models Thesetoolsprovideearlyalertsthatprevent potentialnon-compliancewithEnvironmentalProtection Agency(EPA)regulationsandmaintaincontinuous alignmentwithISO14001standards
Formaintenanceoptimization,heemployssensor-based conditionmonitoringwithmachine-learningalgorithmsto anticipatefailuresbeforetheyoccur,reducingdowntime, conservingresources,andimprovingworkersafetyin accordancewithDOE/FEMPreliabilityprinciples
HisintegrationofAI-drivenstatisticalprocesscontrol (SPC)withprojectandprocessmanagement methodologiesautomatesdefect-detectionandrootcauseanalysis,reducingscrapratesandenergywaste
Thomazalsoadvanceslogisticssustainabilitythrough route-optimizationalgorithmsthatmergeoperational KPIswithcarbon-footprintdata,reducingfuel consumptionandaligningwithDOE’senergy-efficiency goals Hiscareerillustrateshowintelligentdataintegration canconvertindustrialcomplexityintocompetitive advantage,deliveringtraceable,auditableresultsthat benefitbothproductivityandtheplanet
InterviewbyAnaPaulaMontanha,Editor-in-Chief
As part of Human Capital’s ongoing series on executive leadership and industry transformation, Editor-in-Chief Ana Paula Montanha speaks with experts shaping the future of their fields. In this edition, Ana Paula Montanha interviews Thomaz Antunes Espindola Mendes da Mota, a Brazilian Engineer with a specialization in Environmental and Production Management whose career bridges technical excellence, strategic leadership, and sustainability-driven innovation. Mr. Mota has distinguished himself as a visionary in the optimization of processes, waste management, quality systems, and environmental performance. His insights shed light on how engineering precision, data-driven management, and sustainable practices can converge to redefine value creation and long-term economic resilience
1.HowcanautomationandAIcontributetomoreaccurate faultpredictioninprocessandindustrialenvironments? Predictivealgorithmsanalyzeprocessandsensordatain realtime,identifyinganomaliesbeforetheyevolveinto failures Bycorrelatingvibration,temperature,andflow patternswithhistoricalmaintenancedata,AIsystemscan reducemeantimebetweenfailures(MTBF) Whenapplied undertheappropriateframeworks,thesetoolsminimize unplannedstoppagesandenhanceoverallsafety
2.Whatistheconnectionbetweenenvironmental managementandAIinproductionengineering?
Environmentalperformanceisincreasinglydata-driven AI allowsreal-timetrackingofenergyuse,emissions,and wastegenerationandmanagement,ensuringcompliance withISO14001requirements Thesamedatathatimproves processefficiencycanalsoverifysustainabilityoutcomes
3.Whatbarriersdoindustriesfacewhen implementingAI-basedoptimizationsystems? Thetwomainobstaclesaredataqualityandcultural resistance.Manyplantscollectlargeamountsofdata withoutvalidationoranalyticsexpertise.Engineers specializedintheimprovementofprocessesplayakey roleinbuildingdataintegrityandfosteringcrossfunctionalcollaboration
4 HowcanengineersensureAIapplicationsremain trustworthyandauditable?
TrustworthyAIrequirestransparencyandtraceability FollowingNIST’sTrustworthyandResponsibleAI principles,thatareexplainability,accountability,andrisk management,helpsensurethatAImodelscomplement ratherthanreplaceengineeringjudgment
5.Whatadvicewouldyougivetoprofessionals integratingenvironmentalmanagementwithAIdrivenmanufacturing?
Startsmallbutstructured:focusonenergy-intensiveor high-scrapprocesses,gatherreliabledata,anddefine KPIsthatconnectproductivitytosustainability Collaborationamongengineering,IT,andEHSteams ensuresbalancedoutcomes
6.WhichU.S.sectorsaremostalignedwiththis integratedexpertise?
Advancedmanufacturing,automotive,energy,and logisticssectorsareleadingdigitaltransformation BLS (2024)datashowsustainedhiringforprocessengineers intheseareas,whileDOEandEPAprogramsprovide strongincentivesforcleaner,moreefficientproduction
FUTUREOUTLOOKANDRECOMMENDATIONS
TheoutlookforprocessengineersintheUnitedStates remainsrobustasautomation,AI,andsustainability becomeindustrialcornerstones.TheBLS(2024)projects 11%employmentgrowththrough2034,underscoringthe profession’sstrategicimportanceinproductivityand environmentalstewardship
TheEPA(2024a)reportsthatover7,500facilitiesemitted 258billionmetrictonsofCO₂ein2023,emphasizingthe needforpredictivecontrolandreliabledatasystems The EIA(2025)confirmsthatmanufacturingconsumed20.7 quadrillionBTUsin2022,aboutone-quarterofUS energy use,highlightingthepotentialforefficiencygains
DOE’sAdvancedMaterials&ManufacturingTechnologies Office(AMMTO)promotesR&Dandworkforcetrainingto enhancemanufacturingperformance NIST’s2024launch ofa$70millionManufacturingUSAInstitutefocusedon AIintegrationunderscoresthefederalcommitmentto transparent,auditable,andsecureAImodels,areaswhere processengineersareuniquelyqualifiedtolead
Organizationsshouldinvestindataliteracyandintegrate AIgovernanceintoISO9001/14001systems,ensuring explainableandaccountableautomation
ApplyingDOE/FEMPpredictive-maintenance guidelinescanreducecostsandemissions,whiledigital dashboardstrackingOEE,energyintensity,andcarbon metricsofferexecutivesreal-timedecisionintelligence
AstheNationalAssociationofStateEnergyOfficials (2024)affirms,improvingmanufacturingenergy efficiencydrivesbothprosperityandsustainability Lookingtoward2035,US competitivenesswilldepend onunitingautomation,environmentalresponsibility, anddataintegrity,anintegrationthatprofessionalslike Mr Motaalreadyembody
